Triple
T110265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sunnyside, Tarrytown, New York |
E2232
|
entity |
| Predicate | hasLandscapeDesign |
P1479
|
FINISHED |
| Object | picturesque style |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: picturesque style | Statement: [Sunnyside, Tarrytown, New York, hasLandscapeDesign, picturesque style]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandscapeDesign Context triple: [Sunnyside, Tarrytown, New York, hasLandscapeDesign, picturesque style]
-
A.
hasDesign
Indicates that one entity possesses, embodies, or is characterized by a particular design associated with another entity.
-
B.
landscapeStyle
chosen
Indicates the design style or aesthetic approach applied to a landscape or outdoor environment.
-
C.
hasDiverseLandscape
Indicates that an entity possesses a variety of distinct physical or environmental features within its geographic area.
-
D.
hasSoil
Indicates that one entity possesses, contains, or is associated with a particular type or instance of soil.
-
E.
hasNatureDesignation
Indicates that something has been formally assigned a specific conservation, protection, or natural-area status or designation.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a258b58efc8190959c86f73d67b744 |
completed | Feb. 28, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69a25641058c8190b5b64509b35d8176 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.